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Hierarchial Clustering Q2

*The author of this computation has been verified*
R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Wed, 12 Nov 2008 14:21:39 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr.htm/, Retrieved Wed, 12 Nov 2008 21:23:33 +0000
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr.htm/},
    year = {2008},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
Hierarchial Clustering
 
Dataseries X:
» Textbox « » Textfile « » CSV «
110.1 66.9 91 97.1 98.1 117 108.8 120.7 112.6 98.3 129.6 113.2 127.9 113.8 114.8 113.5 105.5 112.4 107.8 107.8 113.3 77.8 93.1 103.2 107.9 110.1 102.1 107.5 103.3 112.7 107.4 97 107.3 101.2 100.2 110.1 95.5 114.8 107.7 96.9 112.5 99.3 120.8 110.4 96.6 106 86.4 112.2 101.9 95.5 117.6 92.4 123.3 115.9 96.9 117.8 85.7 100.6 89.9 99.7 113.5 61.9 86.7 88.6 105.1 121.2 104.9 123.6 117.2 106.1 130.4 107.9 125.3 123.9 106.2 115.2 95.6 111.1 100 103.9 117.9 79.8 98.4 103.6 109.2 110.7 94.8 102.3 94.1 110.5 107.6 93.7 105 98.7 98 124.3 108.1 128.2 119.5 94.1 115.1 96.9 124.7 112.7 90.2 112.5 88.8 116.1 104.4 89.5 127.9 106.7 131.2 124.7 91.2 117.4 86.8 97.7 89.1 98.2 119.3 69.8 88.8 97 103.7 130.4 110.9 132.8 121.6 103.9 126 105.4 113.9 118.8 106.5 125.4 99.2 112.6 114 107.2 130.5 84.4 104.3 111.5 111 115.9 87.2 107.5 97.2 111.8 108.7 91.9 106 102.5 101.5 124 97.9 117.3 113.4 95.3 119.4 94.5 123.1 109.8 92.7 118.6 85 114.3 104.9 93.5 131.3 100.3 132 126.1 96.2 111.1 78.7 92.3 80 102.1 124.8 65.8 93.7 96.8 102.3 132.3 104.8 121.3 117.2 127.9 126.7 96 113.6 112.3 130.8 131.7 103.3 116.3 117.3 134.9 130.9 82.9 98.3 111.1 141.9 122.1 91.4 111.9 102.2 124.6 113.2 94.5 109.3 104.3 118 133.6 109.3 133.2 122.9 115.1 119.2 92.1 118 107.6 111.2 129.4 99.3 131.6 121.3 113.5 131.4 109.6 134.1 131.5 115.2 117.1 87.5 96.7 89 119.4 130.5 73.1 99.8 104.4 116 132.3 110.7 128.3 128.9 115.7 140.8 111.6 134.9 135.9 121.1 137.5 110.7 130.7 133.3 120.8 128.6 84 107.3 121.3 125.2 126.7 101.6 121.6 120.5 124 120.8 102.1 120.6 120.4 119.1 139.3 113.9 140.5 137.9 119.2 128.6 99 124.8 126.1 113.9 131.3 100.4 129.9 133.2 113.3 136.3 109.5 159.4 151.1 116.8 128.8 93.1 111 105 114.8 133.2 77 110.1 119 119.2 136.3 108 132.7 140.4 117.8 151.1 119.9 135 156.6 122.5 145 105.9 118.6 137.1 125.1 134.4 78.2 94 122.7 125 135.7 100.3 117.9 125.8 125.1 128.7 102.2 114.7 139.3 121.2 129.2 97 113.6 134.9 118.9 138.6 101.3 130.6 149.2 109.8 132.7 89.2 117.1 132.3 109.2 132.5 93.3 123.2 149 109 137.3 88.5 106.1 117.2 110.9 127.1 62.2 87.9 116.2 112.5
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'George Udny Yule' @ 72.249.76.132


Summary of Dendrogram
LabelHeight
13.55949434611153
25.22589705218157
35.85385019978483
46.01581249707803
56.43972049082879
66.53222779762003
77.29040465269247
87.42293742395827
97.7051930540383
107.75112895003045
117.97370679169983
128.001249902359
138.37675354776538
148.43445315358381
158.50058821494137
168.70804225988828
178.75328509760764
189.10878780157116
199.20244890347828
209.22074667891295
219.55981171362701
229.93931587182941
2310.6886076472774
2410.9219961545498
2511.0968463988649
2611.1022520238013
2711.5387679774247
2811.9812353286295
2912.1485238810851
3012.4630199539865
3112.5159897730863
3212.6933732419447
3312.7232071428551
3412.9327782434657
3513.2778010227598
3613.8706261456448
3716.1877658136178
3816.4432444264393
3916.4556563508604
4016.8257176018251
4117.3246036494697
4218.0926901504162
4318.5460971915411
4419.2980988184615
4519.7264910609359
4619.8626044828014
4720.5783867200517
4821.1548365802976
4922.0460266334611
5025.3856489850655
5125.9538630751251
5226.1483676792489
5328.0010737240974
5430.0519525358814
5531.3894886865014
5634.4427361073134
5735.7677815929308
5835.8075805043027
5936.1443808091085
6042.5006787151671
6143.438866683393
6244.847311681285
6351.1426642805709
6459.5282204812653
6566.7711550432266
6680.8024093157599
6792.4473793897082
68115.345813332353
69149.596098950422
70212.144261567956
71219.046075446177
72661.482319874866
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr/1muzc1226524890.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr/1muzc1226524890.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr/2kehf1226524890.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t122652501016a6dxfrb7goosr/2kehf1226524890.ps (open in new window)


 
Parameters (Session):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
Parameters (R input):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
R code (references can be found in the software module):
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == 'TRUE'){
dum = xlab
xlab = ylab
ylab = dum
}
x <- t(y)
hc <- hclust(dist(x),method=par1)
d <- as.dendrogram(hc)
str(d)
mysub <- paste('Method: ',par1)
bitmap(file='test1.png')
if (par4 == 'TRUE'){
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
if (par2 != 'ALL'){
if (par3 == 'TRUE'){
ylab = 'cluster'
} else {
xlab = 'cluster'
}
par2 <- as.numeric(par2)
memb <- cutree(hc, k = par2)
cent <- NULL
for(k in 1:par2){
cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE]))
}
hc1 <- hclust(dist(cent),method=par1, members = table(memb))
de <- as.dendrogram(hc1)
bitmap(file='test2.png')
if (par4 == 'TRUE'){
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
str(de)
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- length(x[,1])-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,hc$labels[i])
a<-table.element(a,hc$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
if (par2 != 'ALL'){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- par2-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,hc1$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
 




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